Nineteen Imperial fellows showcased research projects aimed at tackling global health problems and disease challenges at a special celebration event.
The Imperial 4i Clinician Scientist Training Scheme Celebration event took place last month at Imperial’s South Kensington Campus. Fellows on the programme presented and showcased posters of a range of research projects icluding work in cardiology, rheumatology, infectious diseases and microbiology to an audience of senior academics and clinicians at Imperial College London and Imperial College Healthcare NHS Trust.
The Imperial Immunity, Inflammation, Infection and Informatics (Imperial 4i) Clinician Scientists Training Scheme provides funding and support for doctors in clinical training to undertake a PhD. Dr James Howard, Dr Laura Watts and Dr Ruthiran Kugathasan were some of the research fellows who presented their projects:
Using AI to better identify pacemakers in emergencies
Dr James Howard is developing software called a Neural Network that can identify cardiac rhythm devices in x-rays more accurately and quickly than current methods.
More than one million people around the world have a cardiac rhythm device implanted each year - over 50,000 per year in the UK. These devices are placed under the patients’ skin to either help the heart’s electrical system function properly or measure heart rhythm. Pacemakers treat slow heart rhythms by ‘pacing’ the heart to beat faster, whilst defibrillators treat fast heart rhythms by delivering electric shocks to reset the heartbeat back to a normal rhythm.
In some rare cases these devices can fail and patients can deteriorate as a result. When this occurs clinicians need to determine the model of a device to investigate why it failed. Unless they have access to the records where implantation took place, or the patient can tell them, staff must use a flowchart algorithm to identify pacemakers by a process of elimination. This method can be time consuming these flow charts are now outdated and therefore inaccurate. This can result in delays to delivering care to patients, who are often in critical conditions.
Dr Howard has trained a Neural Network to identify more than 1,600 different cardiac devices. To use the neural network, the clinician uploads the X-ray image containing the device into a computer and the software reads the image to give a result on the make and model of the device within seconds.
To test the technology, he explored whether it could identify the devices from radiographic images of more than 1,500 patients at Hammersmith Hospital, part of Imperial College Healthcare NHS Trust, between 1998 and 2018. He then compared the results with five cardiologists who used the current flowchart algorithm to identify the devices.
He found that the software outperformed current methods. It was 99 percent accurate in identifying the manufacturer of a device, compared with only 72 percent accuracy for the flow chart. Dr Howard believes the software could greatly speed up the care of patients with heart rhythm device problems.
The role of genes and osteoporosis
Dr Laura Watts, Clinical Research Fellow at the College and Imperial College Healthcare NHS Trust, presented her work on a gene called FUBP3 and its link to osteoporosis.
Osteoporosis weakens bones, making them fragile and more likely to break. It develops slowly over several years and is often only diagnosed when a fall causes a bone to break.
Women are 50 per cent more likely to develop osteoporosis once they reach 50 than men. This is because menopause causes women to lose bone density rapidly.
Osteoporosis and reduced bone mineral density has a strong genetic component. Several hundred genes have been linked with osteoporosis and bone mineral density but their effect is often unknown.
Dr Watts found that one of these genes is FUBP3. Using a mouse model lacking FUBP3, Dr Watts found that it plays a role in normal bone formation and maintenance. This finding could help identify new potential targets for the treatment of osteoporosis. Dr Watts outlined that she will now carry out future work to explore the mechanisms of how this gene works.
Predicting seasonal flu
Dr Ruthiran Kugathasan displayed a poster presentation about his work exploring how flu evolves and developing models to predict future evolution of the virus, to improve vaccines.
Flu is a common viral illness spread by coughs and sneezes. Seasonal flu results in significant burdens to public health and the economy and the best protection against the flu is vaccination. In the last decade, the H3N2 virus has caused most seasonal flu but continued evolution of the virus means predicting the correct vaccine strain in advance of the upcoming flu season is increasingly difficult.
Dr Kugathasan is working with mathematical modellers at the College to improve upon current models of flu transmission, and with sequencing experts to better understand flu evolution.
He hopes that his work can contribute to better prediction of future seasonal flu transmission and an improvement in vaccine strain selection, which will make the flu vaccine more effective
Developing the next generation of clinician scientists
Professor Matthew Pickering, Co-Director of the Imperial 4i Clinician Scientist Training Scheme, said:
“The aim of the Imperial 4i scheme is to develop the next cohort of clinical academic leaders. This is vital as clinical scientists play a key role in driving innovation in healthcare delivery, disease prevention and the development of new treatments. Our show case event demonstrated the talent and exciting research of our 4i researchers.”
Guests at the event also heard from keynote speaker Professor Sir Mark Walport, Chief Executive of UK Research and Innovation (UKRI), who spoke about the about the future landscape of biomedical science and said:
“The Imperial 4i Clinician Scientists Training Scheme is a fantastic example of the many ways Imperial provides opportunities for talented clinical scientists to carry out cutting-edge research which could help address some of the major health problems we face. It was inspiring to listen to and observe the work carried out by the fellows from the Imperial 4i programme.”
Article text (excluding photos or graphics) © Imperial College London.
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